posted by organizer: Bartosz_Krawczyk || 2183 views || tracked by 14 users: [display]

ECML MLLS 2015 : 2nd Workshop on Machine Learning in Life Sciences


When Sep 11, 2015 - Sep 11, 2015
Where Porto, Portugal
Submission Deadline Jun 22, 2015
Notification Due Jul 13, 2015
Final Version Due Jul 27, 2015
Categories    machine learning   data mining   medical informatics   bioinformatics

Call For Papers

2nd Workshop on Machine Learning in Life Sciences

to be organized under:

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015

Life sciences, ranging from medicine, biology and genetics to biochemistry and pharmacology have developed rapidly in previous years. Computerization of those domains allowed to gather and store enormous collections of data. Analysis of such vast amounts of information without any support is impossible for human being. Therefore recently machine learning and pattern recognition methods have attracted the attention of broad spectrum of experts from life sciences domain.
The aim of this Workshop is to stress the importance of interdisciplinary collaboration between life and computer sciences and to provide an international forum for both practitioners seeking new cutting-edge tools for solving their domain problems and theoreticians seeking interesting and real-life applications for their novel algorithms. We are interested in novel machine learning technologies, designed to tackle complex medical, biological, chemical or environmental data that take into consideration the specific background knowledge and interactions between the considered problems. We look for novel applications of machine learning and pattern recognition tools to contemporary life sciences problems, that will shed light on their strengths and weaknesses. We are interested in new methods for data visualization and methods for accessible presentation of results of machine learning analysis to life scientists. We welcome new findings in the intelligent processing of non-stationary medical, biological and chemical data and in proposals for efficient fusion of information coming from multiple sources. Papers on efficient analysis and classification of bid data (understood as both massive volumes and high-dimensionality problems) will be of special interest to this Workshop.

Topics of interest:
• novel machine learning and pattern recognition models for analyzing medical, biological and chemical data;
• new models for efficient, fast and effective processing of big, massive and multi-dimensional life sciences data;
• intelligent methods for analysis of microarrays, gene and protein modeling, biological networks, docking etc;
• automatic drug design with machine learning methods, QSAR / QSPR modeling;
• methods for data visualization and accessible presentation of machine learning results / findings to domain experts (doctors, biologists, chemists etc);
• new developments in ensemble, compound and hybrid classification for life sciences;
• methods for incorporating background knowledge into machine learning systems;
• recent developments in complex data pre-processing: feature selection, noise filtering, class imbalance etc;


Together with The Group of Machine Learning Research at the Jagiellonian University in Cracow, represented by Wojciech Czarnecki, Igor Podolak, Jacek Tabor in cooperation with the Institute of Pharmacology, Polish Academy of Sciences, Cracow, represented by Andrzej Bojarski, Sabina Smusz we are proud to present a competition with objective to predict the activity of selected chemical structures against a set of given proteins. The details of the challenge, together with dataset and submission system can be found here:

Winner of the competition will receive three types of prizes:
★ Registration fee for the ECML-PKDD 2015 conference (whole conference) will be reimbursed.
★ Authors will give an oral presentation of their method during workshop and paper describing their approach will appear in the proceedings.
★ Extended version of the paper will be included in the post workshop special issue of a journal (with IF)1).

Submission details:
+ format: Springer LNCS (please referer to the author guides of the ECML main track)
+ page limit: 12 pages
+ proceedings will be published online with ISBN
+ submitt via the EasyChair:

Workshop funding:
This Workshop will be supported by EC under FP7, Coordination and Support Action, Grant Agreement Number 316097, ENGINE European Research Centre of Network Intelligence for Innovation Enhancement:

To contribute to the success of the Workshop, the ENGINE Centre will finance the conference fee for 10 authors of the best papers accepted for this Workshop (up to 500 euro each). This will most certainly be an attractive opportunity for researches who want to disseminate their high-quality research findings.

Journal Special Issue:
Extended versions of accepted papers will be invited to special issue of a journal (with IF)1, we are currently finishing negotiations with a potential venue).

Workshop chairs:
Bartosz Krawczyk, Wroclaw University of Technology, Poland

Prof. Michał Woźniak, Wroclaw University of Technology, Poland

Important dates:
Workshop paper submission deadline June 22, 2015
Workshop paper acceptance notification July 13, 2015
Workshop paper camera-ready deadline July 27, 2015

Related Resources

ECML-PKDD 2017   European Conference on Machine Learning and Principles and Practice of Knowledge Discovery
ETHE Blearning 2017   Blended learning in higher education: research findings
ACML 2017   The 9th Asian Conference on Machine Learning
DSAA 2017   The 4th IEEE International Conference on Data Science and Advanced Analytics 2017
ICMLA 2017   16th IEEE International Conference On Machine Learning And Applications
NIPS 2017   The Thirty-first Annual Conference on Neural Information Processing Systems
ICPR 2018   24th International Conference on Pattern Recognition
DMBD 2017   DMBD'2017:Call for Papers (Jan. 30, 2017)
ICDM 2017   IEEE International Conference on Data Mining 2017
ICONIP 2017   International Conference on Neural Information Processing